import pandas as pd, altair as alt
url = "https://raw.githubusercontent.com/SpencerShelton/Test/master/games.csv"
games = pd.read_csv(url)
alt.data_transformers.enable('default', max_rows=None)

DataTransformerRegistry.enable('default')

This dataset is created from a set of chess games from the website Lichess.org. I am interested in exploring the categorical variables of opening_name and winner and the categorical variables turns and white_rating

alt.Chart(games).transform_density(
    'white_rating',
    as_=['white_rating', 'density'],
).mark_area().encode(
    x="white_rating:Q",
    y='density:Q',
)

alt.Chart(games).transform_density(
    'turns',
    as_=['turns', 'density'],
).mark_area().encode(
    x="turns:Q",
    y='density:Q',
)

winners = [0,0,0]
winnderLabels = ["White", "Black", "Draw"]
for e in games["winner"]:
  if e == "white":
    winners[0]+=1
  elif e == "black":
    winners[1]+=1
  else:
    winners[2]+=1

winnerData = pd.DataFrame({"Number": winners, "Winner": winnderLabels})
alt.Chart(winnerData).mark_bar().encode(
    alt.X("Winner"),
    alt.Y("Number"))

openingLabels = games["opening_name"].unique().tolist()
number = [0]
for e in games["opening_name"]:
  if openingLabels.index(e) >= len(number):
    number.insert(openingLabels.index(e),1)
  else:
    number[openingLabels.index(e)]+=1

openingData = pd.DataFrame({"Number": number, "Name": openingLabels})
alt.Chart(openingData).mark_bar().encode(
    alt.X("Name"),
    alt.Y("Number"))